A Proposed Method for Residual Citation Allocation Based on Citation Contexts’ Similarity

This article proposes an approach for allocating residual citations to scientific publications and demonstrating this proposed approach with a sample of biomedical publications. Residue citations (i.e., citations that are lost due to citation practices termed “Obliteration by Incorporation” and the “Palimpsestic Syndrome”) in consequent citations in the second, third or nth generations are then reconstituted. The proposed approach takes into account citation contexts (i.e., the contribution of a cited publication) for allocating residual citation. The proposed method for allocating residual citation is based on the similarity between the citation contexts of a publication and those of its nth generation citations in their n+1th generation citations. The proposed method was demonstrated using a sample with ten base articles and their five generations of citations, from which 5,272 citation context pairs were obtained. The proposed indirect citation weighting was compared with the existing cascading citation weighting method using one T-test. Statistical tests were also performed to understand the differences in the residual citations from one generation to the other. Like the cascading citation system, residual citations from articles to their generations of citations decreased as the number of generations increased. However, residue citations accrued to publications at all the generations were statistically different between the proposed residual citation and the cascading citation system. This study proposes a method for assessing scientific communication based on the contribution of scientific publications beyond the conventional direct citation.

Relationships between method-section citation rates and citation contexts: evidence from highly cited references in psychology

PurposeThe Method section of research articles offers an important space for researchers to describe their research processes and research objects they utilize. To understand the relationship between these research materials and their representations in scientific publications, this paper offers a quantitative examination of the citation contexts of the most frequently cited references in the Method section of the paper sample, many of which belong to the category of research material objects.Design/methodology/approachIn this research, the authors assessed the extent to which these references appear in the Method section, which is regarded as an indicator of the instrumentality of the reference. The authors also examined how this central measurement is connected to its other citation contexts, such as key linguistic attributes and verbs that are used in citation sentences.FindingsThe authors found that a series of key linguistic attributes can be used to predict the instrumentality of a reference. The use of self-mention phrases and the readability score of the citances are especially strong predictors, along with boosters and hedges, the two measurements that were not included in the final model.Research limitations/implicationsThis research focuses on a single research domain, psychology, which limits the understanding of how research material objects are cited in different research domains or interdisciplinary research contexts. Moreover, this research is based on 200 frequently cited references, which are unable to represent all references cited in psychological publications.Practical implicationsWith the identified relationship between instrumental citation contexts and other characteristics of citation sentences, this research opens the possibility of more accurately identifying research material objects from scientific references, the most accessible scholarly data.Originality/valueThis is the first large-scale, quantitative analysis of the linguistic features of citations to research material objects. This study offers important baseline results for future studies focusing on scientific instruments, an increasingly important type of object involved in scientific research.Peer reviewThe peer review history for this article is available at: 10.1108/OIR-03-2021-0171

Continued Use of Retracted Papers: Temporal Trends in Citations and (Lack of) Awareness of Retractions Shown in Citation Contexts in Biomedicine

We present the first database-wise study on the citation contexts of retracted papers, which covers 7,813 retracted papers indexed in PubMed, 169,434 citations collected from iCite, and 48,134 citation contexts identified from the XML version of the PubMed Central Open Access Subset. Compared with previous citation studies that focused on comparing citation counts using two time frames (i.e., pre-retraction and post-retraction), our analyses show the longitudinal trends of citations to retracted papers in the past 60 years (1960-2020). Our temporal analyses show that retracted papers continued to be cited, but that old retracted papers stopped being cited as time progressed. Analysis of the text progression of pre- and post-retraction citation contexts shows that retraction did not change the way the retracted papers were cited. Furthermore, among the 13,252 post-retraction citation contexts, only 722 (5.4%) citation contexts acknowledged the retraction. In these 722 citation contexts, the retracted papers were most commonly cited as related work or as an example of problematic science. Our findings deepen the understanding of why retraction does not stop citation and demonstrate that the vast majority of post-retraction citations in biomedicine do not document the retraction. Peer Review https://publons.com/publon/10.1162/qss_a_00155

Topic Modeling of the Research Papers' Citation Contexts: a Structure of an Author's Research Consumption

Citation contexts from research papers, as a rule, contain information about the reasons and the character of using the cited research outputs. By extracting this information from the citation contexts, one can create different data sets for scientometric studies. The paper systematizes general possibilities of using data from the citation contexts for the development of the author-citation network analysis. As one of applications, the paper presents an approach to constructing the thematic structure of a research consumption based on topic modelling of the citation contexts from researchers papers. The thematic structure features built in the forms of a "word tree" and a flowchart are discussed. Possible directions of development of this approach are considered. The proposed thematic structure of the research consumption is a promising new data source for both scientometric studies and creation of new research services.

Content Characteristics of Knowledge Integration in the eHealth Field: An Analysis Based on Citation Contexts

Purpose This study attempts to disclose the characteristics of knowledge integration in an interdisciplinary field by looking into the content aspect of knowledge. Design/methodology/approach The eHealth field was chosen in the case study. Associated knowledge phrases (AKPs) that are shared between citing papers and their references were extracted from the citation contexts of the eHealth papers by applying a stem-matching method. A classification schema that considers the functions of knowledge in the domain was proposed to categorize the identified AKPs. The source disciplines of each knowledge type were analyzed. Quantitative indicators and a co-occurrence analysis were applied to disclose the integration patterns of different knowledge types. Findings The annotated AKPs evidence the major disciplines supplying each type of knowledge. Different knowledge types have remarkably different integration patterns in terms of knowledge amount, the breadth of source disciplines, and the integration time lag. We also find several frequent co-occurrence patterns of different knowledge types. Research limitations The collected articles of the field are limited to the two leading open access journals. The stem-matching method to extract AKPs could not identify those phrases with the same meaning but expressed in words with different stems. The type of Research Subject dominates the recognized AKPs, which calls on an improvement of the classification schema for better knowledge integration analysis on knowledge units. Practical implications The methodology proposed in this paper sheds new light on knowledge integration characteristics of an interdisciplinary field from the content perspective. The findings have practical implications on the future development of research strategies in eHealth and the policies about interdisciplinary research. Originality/value This study proposed a new methodology to explore the content characteristics of knowledge integration in an interdisciplinary field.

The re-instrumentalization of the Diagnostic and Statistical Manual of Mental Disorders (DSM) in psychological publications: a citation context analysis

Research instruments play significant roles in the construction of scientific knowledge, even though we have only acquired very limited knowledge about their lifecycles from quantitative studies. This paper aims to address this gap by quantitatively examining the citation contexts of an exemplary research instrument, the Diagnostic and Statistical Manual of Mental Disorders ( DSM), in full-text psychological publications. We investigated the relationship between the citation contexts of the DSM and its status as a valid instrument being used and described by psychological researchers. We specifically focused on how this relationship has changed over the DSM’s citation histories, especially through the temporal framework of its versions. We found that a new version of the DSM is increasingly regarded as a valid instrument after its publication; this is reflected in various key citation contexts, such as the use of hedges, attention markers, and the verb profile in sentences where the DSM is cited. We call this process the re-instrumentalization of the DSM in the space of scientific publications. Our findings bridge an important gap between quantitative and qualitative science studies and shed light on an aspect of the social process of scientific instrument development that is not addressed by the current qualitative literature.

A Glimpse of the First Eight Months of the COVID-19 Literature on Microsoft Academic Graph: Themes, Citation Contexts, and Uncertainties

As scientists worldwide search for answers to the overwhelmingly unknown behind the deadly pandemic, the literature concerning COVID-19 has been growing exponentially. Keeping abreast of the body of literature at such a rapidly advancing pace poses significant challenges not only to active researchers but also to society as a whole. Although numerous data resources have been made openly available, the analytic and synthetic process that is essential in effectively navigating through the vast amount of information with heightened levels of uncertainty remains a significant bottleneck. We introduce a generic method that facilitates the data collection and sense-making process when dealing with a rapidly growing landscape of a research domain such as COVID-19 at multiple levels of granularity. The method integrates the analysis of structural and temporal patterns in scholarly publications with the delineation of thematic concentrations and the types of uncertainties that may offer additional insights into the complexity of the unknown. We demonstrate the application of the method in a study of the COVID-19 literature.

Exploring multiple diversification strategies for academic citation contexts recommendation

Purpose Citation contexts have been found useful in many scenarios. However, existing context-based recommendations ignored the importance of diversity in reducing the redundant issues and thus cannot cover the broad range of user interests. To address this gap, the paper aims to propose a novelty task that can recommend a set of diverse citation contexts extracted from a list of citing articles. This will assist users in understanding how other scholars have cited an article and deciding which articles they should cite in their own writing. Design/methodology/approach This research combines three semantic distance algorithms and three diversification re-ranking algorithms for the diversifying recommendation based on the CiteSeerX data set and then evaluates the generated citation context lists by applying a user case study on 30 articles. Findings Results show that a diversification strategy that combined “word2vec” and “Integer Linear Programming” leads to better reading experience for participants than other diversification strategies, such as CiteSeerX using a list sorted by citation counts. Practical implications This diversifying recommendation task is valuable for developing better systems in information retrieval, automatic academic recommendations and summarization. Originality/value The originality of the research lies in the proposal of a novelty task that can recommend a diversification context list describing how other scholars cited an article, thereby making citing decisions easier. A novel mixed approach is explored to generate the most efficient diversifying strategy. Besides, rather than traditional information retrieval evaluation, a user evaluation framework is introduced to reflect user information needs more objectively.